Spatial Analysis of Neo-tectonic Signatures in Lower Subansiri Sub-basin using Morphometric Parameters and Fuzzy-AHP

The present study investigates the neo-tectonic signatures in the Lower Subansiri River sub-basin, a geo-dynamically active segment of the Eastern Himalayan Syntaxis. Remote Sensing and GIS-based morphometric analyses were conducted across twenty-four selected indices, such as the Bifurcation Ratio (Rbm), Elongation Ratio (Re), and Stream Length Gradient (Slg), categorized into linear, areal, and relief aspects. Interpolation methods play a key role in geospatial analysis by predicting unknown spatial values from known data points, enabling the generation of continuous tectonic deformation maps. The study area was divided into uniform grid cells using GIS tools, and morphometric indices were computed for each grid to generate thematic maps based on the defined parameters. The Fuzzy Analytic Hierarchy Process (FAHP) was employed to prioritize and integrate the selected indices by ranking tectonic signatures through pairwise comparison and fuzzy logic, calibrated with real-world spatial parameters such as slope, elevation, relief, and drainage density. The resulting prioritized weightages are unitless and classified into five categories of neo-tectonic signatures: very low (3.8–4.7), low (4.7–5.1), medium (5.1–5.5), high (5.5–5.9), and very high (5.9–7.3). The majority of the Lower Subansiri sub-basin falls under the high and very high categories, reflecting significant neo-tectonic activity. Ground-truth validation was carried out to confirm that the FAHP-derived weightages accurately reflect the field conditions. Accordingly, 207 field observation points were selected to verify the presence of neo-tectonic signatures within the study area and validated using Kappa method and obtained the accuracy of moderate to perfect agreements between to model vs field visit. This research provides a valuable framework and reference for geoscientists, geomorphologists, policymakers, and planners to develop context-specific and sustainable disaster risk reduction strategies for the region.